Paper List
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Formation of Artificial Neural Assemblies by Biologically Plausible Inhibition Mechanisms
This work addresses the core limitation of the Assembly Calculus model—its fixed-size, biologically implausible k-WTA selection process—by introducing...
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How to make the most of your masked language model for protein engineering
This paper addresses the critical bottleneck of efficiently sampling high-quality, diverse protein sequences from Masked Language Models (MLMs) for pr...
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Module control in youth symptom networks across COVID-19
This paper addresses the core challenge of distinguishing whether a prolonged societal stressor (COVID-19) fundamentally reorganizes the architecture ...
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JEDI: Jointly Embedded Inference of Neural Dynamics
This paper addresses the core challenge of inferring context-dependent neural dynamics from noisy, high-dimensional recordings using a single unified ...
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ATP Level and Phosphorylation Free Energy Regulate Trigger-Wave Speed and Critical Nucleus Size in Cellular Biochemical Systems
This work addresses the core challenge of quantitatively predicting how the cellular energy state (ATP level and phosphorylation free energy) governs ...
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Packaging Jupyter notebooks as installable desktop apps using LabConstrictor
This paper addresses the core pain point of ensuring Jupyter notebook reproducibility and accessibility across different computing environments, parti...
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SNPgen: Phenotype-Supervised Genotype Representation and Synthetic Data Generation via Latent Diffusion
This paper addresses the core challenge of generating privacy-preserving synthetic genotype data that maintains both statistical fidelity and downstre...
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Continuous Diffusion Transformers for Designing Synthetic Regulatory Elements
This paper addresses the challenge of efficiently generating novel, cell-type-specific regulatory DNA sequences with high predicted activity while min...
使用QuPath和OMERO进行全切片和显微镜图像分析
Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
30秒速读
IN SHORT: 使QuPath能够直接分析存储在OMERO服务器中的图像而无需下载整个数据集，克服了大规模研究的本地存储限制。
核心创新
- Methodology Developed a new QuPath extension from scratch with three pixel access APIs (web, Ice, pixel data microservice) for flexible server compatibility
- Methodology Implemented unit testing with automated Docker container creation for OMERO server connections, ensuring software reliability
- Methodology Designed modular architecture separating core logic (headless operation) from GUI components, improving maintainability and scriptability
主要结论
- 自2024年2月以来，该扩展已被下载29,727次，显示了广泛的采用和活跃的用户社区。
- 支持高达20 GB未压缩的全切片图像（120,000 x 60,000像素）以及具有数十个16位/32位通道的荧光多重图像。
- 通过OMERO集成，能够访问包含超过400 TB已发布成像数据的IDR存储库。
摘要: QuPath是用于生物图像分析的开源软件。作为一个灵活且易于安装的桌面应用程序，QuPath被全球实验室用于可视化和分析大型复杂图像。然而，仅依赖存储在本地文件系统上的图像限制了QuPath在更大规模研究中的应用。本文描述了一个新的扩展，使QuPath能够从OMERO服务器访问像素和元数据。这通过允许软件高效处理远程存储的图像来增强其功能，同时也为希望将QuPath连接到其他图像管理系统的开发人员提供了模板。